Using fuzzy set theory to address the uncertainty of susceptibility to drought

This paper presents the technical aspects of a new methodology for assessing the susceptibility of society to drought. The methodology consists of a combination of inference modelling and fuzzy logic applications. Four steps are followed: (1) model input variables are selected—these variables reflect the main factors influencing susceptibility in a social group, population or region, (2) fuzzification—the uncertainties of the input variables are made explicit by representing them as ‘fuzzy membership functions’, (3) inference modelling—the input variables are used to construct a model made up of linguistic rules, and (4) defuzzification—results from the model in linguistic form are translated into numerical form, also through the use of fuzzy membership functions. The disadvantages and advantages of this methodology became apparent when it was applied to the assessment of susceptibility from three disciplinary perspectives: Disadvantages include the difficulty in validating results and the subjectivity involved with specifying fuzzy membership functions and the rules of the inference model. Advantages of the methodology are its transparency, because all model assumptions have to be made explicit in the form of inference rules; its flexibility, in that informal and expert knowledge can be incorporated through ‘fuzzy membership functions’ and through the rules in the inference model; and its versatility, since numerical data can be converted to linguistic statements and vice versa through the procedures of ‘fuzzification’ and ‘defuzzification’.     

To make zero emissions technologies and strategies become a reality,the lessons learned of cleaner production dissemination have to be known

With respect to the philosophy of the preventive approach, the bottom line has often been illustrated with the saying: ‘…a gram of prevention is better than a kilogram of cure…’ But you cannot manage a problem that you do not know. In case of cleaner production, the approach is not to solve the problem but to prevent it. This is a deduction in two ways. Firstly, a new problem has to be present in order to be recognised, also for prevention. Secondly, the problem that has to be prevented is connected to the life-cycle of the capital and technology investments in production processes, products and services. A dilemma for new concepts in general is that pilot studies never meet the full conditions that are needed. When the obstacles of routines are overcome, often the momentum for fully conditioned approaches is passed and watered-down definitions and applications are introduced.     

生物学模型与海洋学模型的耦合

海洋生态系统的动力问题,如可观测的化学-生物量的时空变化是由于生物和物理过程决定的.预报海洋系统的未来发展需要有一个理论框架.如模型,而这个模型是根据对相关的各个不同过程的研究和了解而发展的.从理论上描述海洋系统的自然方法似乎是把化学生物模型与环境模型结合在一起.但是,环境模型相对比较先进,而化学-生物过程的定量理论描述比较落后.本文讨论了一些关于发展相容理论的方法和问题,指出了海洋生物学模型和海洋学模型耦合的潜在盖处.     

Relationship between the lipid content of fish and their bioconcentration potential of 1,2,4-trichlorobenzene

A significant positive correlation between the lipid content of eight fish species and their bioconcentration factor (BCF) of 1,2,4-trichlorobenzene is demonstrated. The log BCF value on a lipid basis is in good agreement with the log n-octanol/water partition coefficient.     

Visualizing mushroom body response to a conditioned odor in honeybees

Combining differential conditioning with optophysiological recordings of bee brain activity allows the investigation of learning-related changes in complex neural systems. In this study we focused on the mushroom bodies of the bee brain. Presenting different odors to the animal leads to significant activation of the mushroom body lips. After differential conditioning, the rewarded odor leads to stronger activation than it did before training. Activation by the unrewarded odor remains unchanged. These results resemble findings in the bee's antennal lobes, which are the first olfactory relay station in the insect brain. As an integrative neural network, enhanced activation of the mushroom body lip may carry additional information, i.e., for processing odor concentrations.